Node Classification on Flickr (test)
92.91AccuracySignGT
Evaluation results
| Method | Links | ||||||
|---|---|---|---|---|---|---|---|
| SignGT2023.10 | 92.91 | — | — | — | — | — | |
| FAGCN2023.10 | 92.19 | — | — | — | — | — | |
| Specformer2023.10 | 92.05 | — | — | — | — | — | |
| GloGNN2023.10 | 91.14 | — | — | — | — | — | |
| NodeFormer2023.10 | 90.97 | — | — | — | — | — | |
| GPRGNN2023.10 | 90.66 | — | — | — | — | — | |
| SGC2023.10 | 86.79 | — | — | — | — | — | |
| GCN2023.10 | 86.37 | — | — | — | — | — | |
| GAT2023.10 | 85.73 | — | — | — | — | — | |
| DREAMNoise Type=uniform2026.01 | 53.84 | — | — | — | — | — | |
| DREAMNoise Type=asymmetric2026.01 | 53.55 | — | — | — | — | — | |
| PSNR-GCNBackbone=GCN2023.05 | 52.47 | — | — | — | — | — | |
| DenseGCNBackbone=GCN2023.05 | 52.18 | — | — | — | — | — | |
| ResGCNBackbone=GCN2023.05 | 51.9 | — | — | — | — | — | |
| JKNetBackbone=GCN2023.05 | 51.65 | — | — | — | — | — | |
| GCNBackbone=GCN2023.05 | 51.4 | — | — | — | — | — | |
| BPTraining Algorithm=Backpropagation2024.06 | 50.79 | — | — | — | — | — | |
| CaFo+MSETraining Algorithm=CaFo with MSE Loss2024.06 | 50.02 | — | — | — | — | — | |
| DFA-GNNTraining Algorithm=Direct Feedback Alignment for GNN2024.06 | 49.8 | — | — | — | — | — | |
| GCNNoise Type=uniform2026.01 | 49.77 | — | — | — | — | — | |
| CaFo+CETraining Algorithm=CaFo with Cross Entropy Loss2024.06 | 49.69 | — | — | — | — | — | |
| GCNNoise Type=asymmetric2026.01 | 49.54 | — | — | — | — | — | |
| PEPITATraining Algorithm=PEPITA2024.06 | 49.28 | — | — | — | — | — | |
| DREAMNoise Type=pair2026.01 | 48.39 | — | — | — | — | — | |
| WholeFull Dataset=true2023.10 | 47.2 | — | — | — | — | — | |
| SP-ESGCRatio (r)=0.10%2026.05 | 47.2 | — | — | — | — | — | |
| SP-ESGCRatio (r)=0.50%2026.05 | 47.2 | — | — | — | — | — | |
| Whole Dataset2026.05 | 47.2 | — | — | — | — | — | |
| GcondRatio (r)=0.50%2023.10 | 47.1 | — | — | — | — | — | |
| GcondRatio (r)=1.00%2023.10 | 47.1 | — | — | — | — | — | |
| SGDDRatio (r)=0.50%2023.10 | 47.1 | — | — | — | — | — | |
| SGDDRatio (r)=1.00%2023.10 | 47.1 | — | — | — | — | — | |
| GcondRatio (r)=1.00%2026.05 | 47.1 | — | — | — | — | — | |
| SFGCRatio (r)=1.00%2026.05 | 47.1 | — | — | — | — | — | |
| SP-ESGCRatio (r)=1.00%2026.05 | 47.1 | — | — | — | — | — | |
| SFGCRatio (r)=0.50%2026.05 | 47 | — | — | — | — | — | |
| SGDDRatio (r)=0.10%2023.10 | 46.9 | — | — | — | — | — | |
| GC-SNTKRatio (r)=0.50%2026.05 | 46.8 | — | — | — | — | — | |
| GC-SNTKRatio (r)=0.10%2026.05 | 46.7 | — | — | — | — | — | |
| SFGCRatio (r)=0.10%2026.05 | 46.6 | — | — | — | — | — | |
| GcondRatio (r)=0.10%2023.10 | 46.5 | — | — | — | — | — | |
| GcondRatio (r)=0.10%2026.05 | 46.5 | — | — | — | — | — | |
| SGDDRatio (r)=0.10%2026.05 | 46.5 | — | — | — | — | — | |
| GC-SNTKRatio (r)=1.00%2026.05 | 46.5 | — | — | — | — | — | |
| SFTraining Algorithm=Selective Feedback2024.06 | 46.47 | — | — | — | — | — | |
| SGDDRatio (r)=0.50%2026.05 | 46.4 | — | — | — | — | — | |
| GDCRatio (r)=0.10%2023.10 | 46.3 | — | — | — | — | — | |
| SGDDRatio (r)=1.00%2026.05 | 46.3 | — | — | — | — | — | |
| GCNIIBackbone=GCN2023.05 | 46.18 | — | — | — | — | — | |
| GDCRatio (r)=0.50%2023.10 | 45.9 | — | — | — | — | — | |
| GCNNoise Type=pair2026.01 | 45.86 | — | — | — | — | — | |
| GDCRatio (r)=1.00%2023.10 | 45.8 | — | — | — | — | — | |
| SimGCRatio (r)=0.50%2026.05 | 45.6 | — | — | — | — | — | |
| SimGCRatio (r)=0.10%2026.05 | 45.3 | — | — | — | — | — | |
| GcondRatio (r)=0.50%2026.05 | 45.2 | — | — | — | — | — | |
| RandomRatio (r)=1.00%2023.10 | 44.6 | — | — | — | — | — | |
| CoarseningRatio (r)=1.00%2023.10 | 44.6 | — | — | — | — | — | |
| RandomRatio (r)=1.00%2026.05 | 44.6 | — | — | — | — | — | |
| CoarseningRatio (r)=0.50%2023.10 | 44.5 | — | — | — | — | — | |
| HerdingRatio (r)=1.00%2023.10 | 44.4 | — | — | — | — | — | |
| HerdingRatio (r)=1.00%2026.05 | 44.4 | — | — | — | — | — | |
| K-CenterRatio (r)=1.00%2023.10 | 44.1 | — | — | — | — | — | |
| K-CenterRatio (r)=1.00%2026.05 | 44.1 | — | — | — | — | — | |
| RandomRatio (r)=0.50%2023.10 | 44 | — | — | — | — | — | |
| RandomRatio (r)=0.50%2026.05 | 44 | — | — | — | — | — | |
| HerdingRatio (r)=0.50%2023.10 | 43.9 | — | — | — | — | — | |
| HerdingRatio (r)=0.50%2026.05 | 43.9 | — | — | — | — | — | |
| SimGCRatio (r)=1.00%2026.05 | 43.8 | — | — | — | — | — | |
| K-CenterRatio (r)=0.50%2023.10 | 43.2 | — | — | — | — | — | |
| K-CenterRatio (r)=0.50%2026.05 | 43.2 | — | — | — | — | — | |
| HerdingRatio (r)=0.10%2023.10 | 42.5 | — | — | — | — | — | |
| HerdingRatio (r)=0.10%2026.05 | 42.5 | — | — | — | — | — | |
| FF+VNTraining Algorithm=Forward-Forward with Vicinal Neighborhood2024.06 | 42.4 | — | — | — | — | — | |
| K-CenterRatio (r)=0.10%2023.10 | 42 | — | — | — | — | — | |
| K-CenterRatio (r)=0.10%2026.05 | 42 | — | — | — | — | — | |
| CoarseningRatio (r)=0.10%2023.10 | 41.9 | — | — | — | — | — | |
| RandomRatio (r)=0.10%2023.10 | 41.8 | — | — | — | — | — | |
| RandomRatio (r)=0.10%2026.05 | 41.8 | — | — | — | — | — | |
| FF+LATraining Algorithm=Forward-Forward with Layer-wise Alignment2024.06 | 6.09 | — | — | — | — | — | |
| ADAEDGEBackbone=GCN2020.06 | — | 61.2 | — | — | — | — | |
| ADAEDGEBackbone=GSAGE2020.06 | — | 57.7 | — | — | — | — | |
| ADAEDGEBackbone=GAT2020.06 | — | 48.2 | — | — | — | — | |
| ADAEDGEBackbone=JK-NET2020.06 | — | 57 | — | — | — | — | |
| AS-GATArchitecture=GAT2020.06 | — | 47.2 | — | — | — | — | |
| AS-GCNArchitecture=GCN2020.06 | — | 50.6 | — | — | — | — | |
| AS-GCN2020.04 | — | 50.4 | — | — | — | — | |
| BGCNBackbone=GCN2020.06 | — | 52.7 | — | — | — | — | |
| BGCNBackbone=GSAGE2020.06 | — | 58.1 | — | — | — | — | |
| BGCNBackbone=GAT2020.06 | — | 46.5 | — | — | — | — | |
| BGCNBackbone=JK-NET2020.06 | — | 53.6 | — | — | — | — | |
| BLISSArchitecture=GAT2025.12 | — | 51.1 | — | — | — | — | |
| BLISSArchitecture=GraphSAGE2025.12 | — | 50.3 | — | — | — | — | |
| CLLabel Rate=0.1%, Backbone=GraphSage2026.05 | — | — | — | — | — | 43.04 | |
| CLLabel Rate=0.2%, Backbone=GraphSage2026.05 | — | — | — | — | — | 42.83 | |
| CLLabel Rate=0.5%, Backbone=GraphSage2026.05 | — | — | — | — | — | 43.31 | |
| CLLabel Rate=1%, Backbone=GraphSage2026.05 | — | — | — | — | — | 43.94 | |
| CLLabel Rate=2%, Backbone=GraphSage2026.05 | — | — | — | — | — | 44.61 | |
| CLLabel Rate=5%, Backbone=GraphSage2026.05 | — | — | — | — | — | 45.02 | |
| CLlabel rate=0.1%, Backbone=GAT2026.05 | — | — | — | — | — | 42.49 | |
| CLlabel rate=0.2%, Backbone=GAT2026.05 | — | — | — | — | — | 42.65 |